The Faster a New Technology Takes Off, the Harder It Falls

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The Faster a New Technology Takes Off, the Harder It Falls

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First, a eulogy: The bell curve is dead.

That familiar model for technology adoption (first popularized by the noted sociologist Everett Rogers) – with clearly defined market segments adopting new technologies in predictable groupings – no longer applies. Following this work, Geoffrey Moore wrote in 1991’s Crossing the Chasm that successful new product introductions followed Rogers’s five discrete stages, moving from early adopters to mainstream users only after crossing a sales “chasm” in which the marketing message changes from the new and exciting to the familiar and incremental.

But today, new products and services enter the market better and cheaper right from the start. So producers can’t rely on a class of early adopters and high margins to build up a war chest to spend on marketing to larger and later markets. For better and for worse, thanks to near-perfect market information, consumers are too savvy for that. Everyone knows right away when some new offering gets it right – or, conversely, gets it wrong.

The bell curve, once useful as a model of product adoption, has lost its value as a planning tool. This kind of disruption has its own unique life cycle, and with it its own best practices for marketing and sales, product enhancement, and eventual product replacement.

Markets take off suddenly, or they don’t take off at all. Since adoption is increasingly all-at-once or never, saturation is reached much sooner in the life of a successful new product. So even those who launch these “Big Bang Disruptors” – new products and services that enter the market better and cheaper than established products seemingly overnight – need to prepare to scale down just as quickly as they scaled up, ready with their next disruptor (or to exit the market and take their assets to another industry).

While every Big Bang Disruptor has its own unique trajectory, the examples in our study suggest a new model for the adoption of better and cheaper innovations, one that is radically different from the traditional view of and Rogers and Geoffrey Moore. The life cycle of Big Bang Disruption looks less like a gently sloping bell curve and more like a cliff: as dangerous to competitors on its way up as it is to innovators on the way down.

We call it, for obvious reasons, “the shark fin.”

The process of Big Bang Disruption begins as a series of low-level, often unrelated experiments with different combinations of component technologies. This relative calm may give incumbents the false sense that nothing is happening, or in any event that whatever might be happening is not doing so quickly enough to warrant a competitive response.

Yet when the right combination of technologies is assembled and paired with the right business model, takeoff is immediate. Customers from a wide range of segments, including mass market consumers, adopt the disruptor as quickly as its producers can supply it. Market penetration is often nearly instantaneous.

Next, as the disruptor quickly approaches saturation, adoption drops at nearly the same pace with which it took off, leading to a period of rapid if uneven decline. During this period, early warning systems, careful planning, and the agility to quickly scale up and then down are essential both to capitalize on the opportunity of a Big Bang Disruptor as well as to survive the chaos it can bring to existing markets.

The Rise and Fall of Microsoft's Kinect
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One example of this process was the introduction of an add-on device for Microsoft’s Xbox 360: the Kinect. It initially sold for $150, but it revolutionized home gaming – capturing the imagination of diehard players and casual gamers alike. And while it appeared to come out of nowhere, antecedents could be seen in and out of the gaming industry. Integrating motion and other sensors with facial recognition, for example, had long been in development in many industries, especially in security systems.

Speech recognition, likewise, had already been used in products and services supporting hands-free computing tasks such as automated phone support and in applications including GM’s in-vehicle OnStar system and the popular Siri, which Apple acquired in 2010. Facial recognition had been used for high-end military applications for years and was the subject of extensive experiments by the advertising industry.

Even other game consoles, notably Sony’s PlayStation 3, had experimented with handheld controllers fitted with motion sensors. Sony’s add-on device, the Move, sold fifteen million units in its first two years.

No one, however, had ever put all these components together or integrated them with a catalog of new games designed specifically to take advantage of the powerful hardware and software Microsoft used for Kinect. The new device looked less like its predecessors than it did a technology from the future.

Kinect was an enormous hit, selling eight million units in just the first sixty days. According to Guinness World Records, that made Kinect the fastest-selling consumer electronic device in history. A little over a year after launch, twenty-four million Kinects had been sold, pushing sales of Xbox 360 consoles and games along with it. In 2010, Microsoft took the top spot in the fiercely competitive console market for the first time since Xbox 360’s launch in 2001.

For Big Bang Disruptors, however, catastrophic success invariably leads to rapid market saturation – and with it decline and sunset. Within six months, the pace of Kinect sales dropped precipitously. Though stragglers continued to buy the product in peaks and valleys over the next year, the product had largely fulfilled its mission in its first ten months. For Microsoft – and other game developers – it was time for another innovation.

Big Bang Disruptors like the Kinect, however, can have second lives as new innovators deconstruct them and recombine their parts into something new. Kinect continues to find unexpected uses outside of gaming, thanks in part to Microsoft’s willingness to make its developer tools and interfaces widely available. Telemedicine researchers in the UK, for example, have adapted Kinect for remote tracking of hand and finger movements to guide patients recovering from strokes. Kinect’s technology is also being used in the construction of miniature satellites, where Kinect will handle in-orbit docking.

Farther afield, the economies of scale that comes from production of millions of Kinect units has made it cost-effective to use some of its components for a fast-evolving market of health, fitness, and monitoring devices. Companies including Fitbit, Jawbone, and Nike, as well as other startups, are selling low-cost wearable computers that use accelerometers and other sensor technology to track and record an increasingly wide range of vital signs and measurements, including steps taken, calories burned, heart rate, temperature, and sleep patterns.

With the shark fin, companies that have long operated as the flippers of their industry, controlling its speed, direction, and destination, suddenly find themselves the pinball, bouncing around at the whim of forces outside their control. To ensure their future as the former and not the latter, they need to understand where Big Bang Disruptors come from, how they enter and exit the market, and what they leave in their wake.

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